Results 161 to 170 of about 839,459 (306)

Explainable deep learning for healthcare workforce attrition: a methodological study on the Watson healthcare synthetic benchmark. [PDF]

Front Public Health
Yin D, Lu X, Mei T.
europepmc   +1 more source

Microfluidic Nano‐Assembly of Red‐Blood‐Cell (RBC) Lipids and Components for Engineering Extracellular Vesicles

Advanced Healthcare Materials, EarlyView.
Engineered red blood cell‐derived extracellular vesicles (eRBCEVs) are synthesized via controlled microfluidic assembly from native RBC lipids, enabling tunable encapsulation of proteins, nucleic acids, nanoparticles, and viral vectors. The platform demonstrates reproducible nanoscale architecture, preserved membrane composition, and functional cargo ...
Chiranth K. Nagaraj, Xilal Y. Rima, Kim T. Nguyen, Courtney Culkins, Nana Boateng, Jacob Doon‐Ralls, Alejandro Bresolin, Xin Huang, Hong Li, Vahedi Amid, Ajeet Pal Singh, Dharti Shantaram, Anastasiia Amari, Mangesh D. Hade, Nicholas R. Merriam, Zachary D. Schultz, Scott Q. Harper, Nizar Y. Saad, Setty M. Magaña, Willa A. Hsueh, Rachel E. Kopec, Blaise R. Kimmel, Andre F. Palmer, Eduardo Reátegui   +23 more
wiley   +1 more source

Predicting End-Stage Renal Disease and Mortality in Chronic Kidney Disease Using Machine Learning: Retrospective Cohort Study. [PDF]

JMIR Med Inform
Chen TH, Lin KH, Ho Y, Tseng WC, Chu YC, Tarng DC.   +5 more
europepmc   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Boosting business [PDF]

Nature, 2014
openaire   +3 more sources

Deep learning-based natural language processing for critical care identification in pediatric emergency department. [PDF]

BMC Emerg Med
Kim JA, Cho S, Hwang M, Lee D, Jeon J, Lee R, Lee C, Kim J, Bae W.   +8 more
europepmc   +1 more source

Encoded Cell‐Material Interactions to Reroute Cytokine Signaling for Regenerative Medicine

Advanced Healthcare Materials, EarlyView.
We present native MATRIX (Material Activated To Regulate Inducible gene eXpression), a co‐engineered material‐cell platform. Surfaces functionalized with antibodies for endogenous soluble ligands (e.g., IL‐1β or IL‐6) capture and immobilize ligands for presentation to a cognate, engineered synthetic Notch receptor, releasing a transcription factor (TF)
Zachary M. Eidman, Jhanvi Sharma, Joanne C. Lee, Nicholas F. Schulze, Hannah J. Brien, Kevin C. Corn, Marjan Rafat, Jonathan M. Brunger   +7 more
wiley   +1 more source

Postherpetic neuralgia risk prediction in hospitalised patients with herpes zoster based on MIMIC-IV. [PDF]

Medicine (Baltimore)
Tang F, Zhao F, Jiang Y, Wang B, Li Y.
europepmc   +1 more source

Mitochondria‐Targeted Nanotherapies in Aging Neurodegenerative Disorders: Emerging Prospects and Clinical Potential

Advanced Healthcare Materials, EarlyView.
Mitochondria‐targeted nanotherapies emerge as a promising strategy for combating aging‐associated neurodegenerative disorders (NDs) by restoring mitochondrial function, reducing oxidative stress, and improving neuronal survival. Recent advances in nanotechnology, therapeutic delivery, and translational research are highlighted, providing insights into ...
Dnyandev G. Gadhave, Ashish B. Jadhav, Nitin B. Waghamode, Shubham Khot, Rajiya Khan, Ravi Hole, Shankar M. Dhobale, Manoj Aswar, Keshav Raj Paudel   +8 more
wiley   +1 more source

An In-Hospital Mortality Risk Model for Patients Undergoing Coronary Artery Bypass Grafting Based on Machine Learning: Cohort Study. [PDF]

JMIR Form Res
Zhu K, Lu W, Liu S, Lin H, Hou J.
europepmc   +1 more source